摘要
在直流电弧炉炼钢过程控制系统中，由于它的复杂机理，高度非线性加大了建模的难度．为提供适用于直流电弧炉炼钢过程优化控制的模型，提出一种引人遗传算法的神经网络建模方法，并将其用于某厂直流电弧炉炼钢过程模型的建立，获得了很好的效果．同时给出了基于现场实测数据的仿真结果．
In process control system for DC arc furnace steelmaking,modelling is a key part.Because ofits complicated mechanism and nonlinearity, it is difficult to model of the process accurately. A genetic neuralnetwork algorithm is presented for DC arc furnace steelmaking process modelling and good effects are obta-ined in its application for real manufacture process modelling.Simulation results with actual process data arepresented.
出处
《北京科技大学学报》
EI
CAS
CSCD
北大核心
1999年第6期588-591,共4页
Journal of University of Science and Technology Beijing
基金
国家"八五"攻关重点课题!No.85-311-02-11-04
关键词
电弧炉
炼钢
模型辨识
遗传算法
神经网络
DC arc furnace
modelling
genetic algorithm(GA)
neural network
